RBF_matlab

matlab linear phase FIR four type amplitude

说明：  用于非期望产出的SBM，衡量企业具有非期望产出的dea模型(SBM for unexpected output, DEA model to measure the unexpected output of enterprises)

为了提高使用精度，研究了某型号MEMS陀螺仪的随机漂移模型。采用游程检验法分析了 该陀螺仪随机漂移数据的平稳性，并根据该漂移为均值非平稳、方差平稳的随机过程的结论， 采用梯度径向基（RBF）神经网络对漂移数据进行了建模。实验结果表明：相比经典RBF网络模 型而言，这种方法建立的模型能更好地描述MEMS陀螺仪的漂移特；相对于季节时间序列模型而 言，其补偿效果提高了大约15％。(In order to improve accuracy, to study a particular model of the MEMS gyroscope random drift model. Using run-length analysis of the test gyro random drift data stationarity, and in accordance with the drift for the average non-stationary, the variance of the random process a smooth conclusion, the use of gradient radial basis (RBF) neural network drift data to build mode. The experimental results show that: compared to the classical RBF network model, this method of establishing a model to better describe the MEMS gyroscope drift special compared with the seasonal time series model, the effect of their compensation increased by approximately 15.)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

时域有限差分方法在一维格子中计算麦克斯韦旋度方程(the finite-difference time-domain solution of Maxwell s curl equations over a one-dimensional space lattice comprised of uniform grid cells)

Particle swarm optimization

计算复杂网络中节点的集聚系数。有详细注释。(Computational complexity of the network node clustering coefficient. There are detailed notes.)

时间序列分析，采用了最小二乘（LS）与自回归(AR)的组合模型，并用MATLAB将其实现(Time series analysis, using a least-squares (LS) and autoregressive (AR) model combination and its implementation using MATLAB)

matlab code to find roots with dechotomie methode

matlab神经网络应用设计--机械工业出版社。6-10章所有程序源码。(matlab neural network application design- Mechanical Industry Publishing House. 6-10 s source code for all programs.)